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SkillsMP は huang-sir1/radiology-skills から 28 件の skill を収集しています。skill を開くとソースと詳細を確認できます。
収集済み skill 28 件中 28 件を表示しています。
Use when an imaging study must map radiology phenotypes or habitats to single-cell, spatial-omics, or pathology-derived cell states across patients, lesions, specimens, regions, or time points. Designs paired, weakly paired, or unpaired cross-modal mapping;…
原文の言語: 英語
Use when multiple imaging centers cannot pool raw data and need a federated-learning research design. Chooses horizontal, vertical, split, or personalized federation; plans aggregation, non-IID handling, site weighting, secure aggregation, differential…
原文の言語: 英語
Use when an imaging study must select, adapt, fine-tune, or audit a pretrained medical imaging or vision-language foundation model. Covers zero-shot evaluation, linear probing, full fine-tuning, adapters, LoRA and other parameter-efficient tuning, prompt…
原文の言語: 英語
Use when a radiology study must jointly model five data dimensions: imaging, clinical, pathology, bulk molecular omics, and single-cell or spatial omics. Selects early, intermediate, late, graph, or latent-factor fusion; handles block-specific preprocessing,…
原文の言語: 英語
Use when designing or auditing an LLM Agent that automates medical-imaging research tasks such as literature and dataset discovery, protocol planning, evidence-grounded RAG, analysis orchestration, reporting checks, manuscript workflows, and reproducible…
原文の言語: 英語
Use when planning, auditing, writing, or revising radiomics, medical imaging AI, and radiology deep learning studies for Radiology/RSNA, Nature-portfolio, Lancet, Cell, npj, European Radiology, or similar venues. Trigger for research frontiers, literature,…
原文の言語: 英語
Design and document ROI/VOI/mask annotation that survives Radiology (RSNA) review — lesion-selection strategy (2D vs 3D, whole-tumour vs largest-slice vs peritumoral vs habitat vs multi-lesion), reader protocol (number, seniority, blinding, independent vs…
原文の言語: 英語
Turn manuscript text, claims, figure/table statements, abstracts, slides, or novelty/comparison assertions into verified, imaging-journal-scoped citation candidates and export one reference-manager-ready file (RIS, EndNote ENW, or BibTeX). Use when the user…
原文の言語: 英語
Prepare and audit Data/Code Availability statements, DICOM de-identification plans, repository selection, dataset citations, and FAIR/sharing checks for Radiology (RSNA) and Nature-portfolio imaging+omics submissions. Use when the user needs a data…
原文の言語: 英語
Design and audit imaging deep-learning studies to Radiology (RSNA) / CLAIM 2024 standard, or to Nature-portfolio / FUTURE-AI trustworthy-AI standard — architecture choice (2D/2.5D/3D CNN, Transformer/ViT, segmentation/detection nets, prognostic models),…
原文の言語: 英語
Assess whether an imaging dataset can support a study and turn it into a complete, submittable design — from feasibility triage to clinical question, target population, endpoint/estimand, minimum-viable vs stronger methods, and a validation strategy (internal…
原文の言語: 英語
Write compliant, non-overstated Ethics, Informed-Consent, and privacy/governance text for imaging and imaging+omics studies — study-type framing (retrospective, prospective, registered, multi-center), IRB/ethics-committee approval and numbers, consent vs…
原文の言語: 英語
Produce publication-quality white-background academic figures for Radiology (RSNA), Nature-portfolio/npj, European Radiology, NEJM, Science, or Lancet-family venues with Python (matplotlib): ROC curves, calibration plots, decision-curve analysis, forest/SROC…
原文の言語: 英語
Find publishable frontier directions and innovation points for imaging-AI / radiomics / radiogenomics research, grounded in the publication patterns of high-impact journals (Radiology, Radiology: AI, Lancet Digital Health, Lancet Oncology, Nature Medicine,…
原文の言語: 英語
Reframe and polish imaging-AI / radiomics / radiogenomics research as a research grant proposal — convert paper-style "we built a model" into grant logic (clinical need → scientific question → hypothesis → specific aims/研究内容 → technical route/技术路线 →…
原文の言語: 英語
Match a finished or near-finished imaging-AI / radiomics / radiogenomics manuscript to the right target journals and build a submission tier list (reach / target / safety) grounded in each venue's publication patterns, author-guide style profiles, and the…
原文の言語: 英語
Turn an imaging-research paper, preprint, PDF, abstract, or reading notes into a concise Chinese .pptx deck for journal club / 读片会 / 组会 / paper sharing. Use when the user wants a paper PPT, journal-club slides, 读片会/文献汇报 slides, or paper-to-slides for an…
原文の言語: 英語
Polish finished imaging-research prose to Radiology (RSNA), Nature-portfolio/npj, European Radiology, NEJM, Science, or Lancet-family house style: concise sentences, correct tense, precise statistical reporting, venue-specific p-value/number/reference style,…
原文の言語: 英語
Run a rigorous pre-submission mock peer review of an imaging-AI / radiomics / radiogenomics manuscript — simulate the methods, statistics, reporting-guideline, figure, citation/claim-verification, and data-sharing reviewer a top journal would assign, and…
原文の言語: 英語
Design, analyse, report, and submit imaging-multi-omics radiogenomics studies that link radiomic/deep imaging phenotypes to genomic, transcriptomic, single-cell, and spatial-omics data. Use when the user mentions radiogenomics, imaging genomics,…
原文の言語: 英語
Design and audit a hand-crafted radiomics study end-to-end to Radiology (RSNA) / CLEAR / IBSI standard — image preprocessing (resampling, intensity normalisation, gray-level discretisation/bin width, filters), IBSI-compliant feature extraction (PyRadiomics or…
原文の言語: 英語
Build full-paper Chinese-English side-by-side (中英对照), figure/table-aware, source-grounded Markdown readers for imaging-research papers from PDF, DOI, arXiv, publisher HTML, or pasted text. Use whenever the user asks to translate or read an imaging paper, make…
原文の言語: 英語
Route an imaging-research manuscript or protocol to the correct reporting/quality guideline and audit it item-by-item for Radiology (RSNA) or Nature-portfolio submission. Use when the user mentions CLAIM, TRIPOD+AI, STARD, PRISMA-DTA, QUADAS-2, CLEAR,…
原文の言語: 英語
Draft, audit, and revise point-by-point reviewer response letters for Radiology (RSNA) and imaging-journal revisions. Use when the user has reviewer comments / a major or minor revision / 审稿意见 to answer for an imaging-AI/radiomics/radiogenomics manuscript.…
原文の言語: 英語
Multi-source literature, dataset, and local-corpus search for imaging research, with deduplication, identifier verification, reference management, and survey/RAG workflow support. Searches PubMed, arXiv, Crossref, and imaging dataset registries (TCIA, GEO,…
原文の言語: 英語
Plan, run, and report imaging biostatistics the way Radiology (RSNA) reviewers expect — diagnostic accuracy with CIs, ROC/AUC comparison (DeLong/bootstrap), reader agreement (Cohen/Fleiss kappa, ICC, Bland-Altman), multi-reader multi-case (MRMC) studies,…
原文の言語: 英語
Move a validated imaging model from retrospective performance toward clinical use — design the clinical-use scenario, model outputs, reader (multi-reader multi-case) studies of radiologist-vs-AI-vs-radiologist+AI, decision thresholds tied to actions,…
原文の言語: 英語
Draft or rebuild imaging-AI / radiomics / radiogenomics manuscript sections for Radiology (RSNA), Nature-portfolio/npj, European Radiology, NEJM, Science, or Lancet-family style from author-provided results, figures, notes, or Chinese drafts. Enforces the…
原文の言語: 英語